TY - JOUR
T1 - Scoring and prediction of early retirement using machine learning techniques: Application to private pension plans
AU - Rocha Salazar, Jose de Jesus
AU - Boado-Penas, María del Carmen
PY - 2019/12/15
Y1 - 2019/12/15
N2 - Artificial intelligence techniques have become very popular in public and private organizations since they allow a more accurate decision-making process. Private insurance companies have ventured into this field by implementing algorithms that allow a better understanding of available data. The knowledge of retirement decisions allows the insurance companies to detect early retirement at a given time so that they have the adequate budgetary provision in place. In this paper, machine learning algorithms and data from private pension plans are used to predict whether a person retires before or after 65 years old in function of both individual characteristics and macroeconomic factors.
AB - Artificial intelligence techniques have become very popular in public and private organizations since they allow a more accurate decision-making process. Private insurance companies have ventured into this field by implementing algorithms that allow a better understanding of available data. The knowledge of retirement decisions allows the insurance companies to detect early retirement at a given time so that they have the adequate budgetary provision in place. In this paper, machine learning algorithms and data from private pension plans are used to predict whether a person retires before or after 65 years old in function of both individual characteristics and macroeconomic factors.
U2 - 10.26360/2019_6
DO - 10.26360/2019_6
M3 - Article
SN - 0534-3232
SP - 119
EP - 145
JO - Anales del Instituto de Actuarios Españoles
JF - Anales del Instituto de Actuarios Españoles
IS - 25
ER -